An Integrated Flight-Deck Decision-Support Tool in an Autonomous Flight Simulation

2011 IEEE/AIAA 30th Digital Avionics Systems Conference

Chamberlain

Wilson

2011

This paper describes a dynamic convective weather avoidance concept that compensates for weather motion uncertainties; the integration of this weather avoidance concept into a prototype 4-D trajectory-based Airborne Separation Assurance System (ASAS) application; and test results from a batch (non-piloted) simulation of the integrated application with high traffic densities and a dynamic convective weather model. The weather model can simulate a number of pseudo-random hazardous weather patterns, such as slow-or fast-moving cells and opening or closing weather gaps, and also allows for modeling of onboard weather radar limitations in range and azimuth. The weather avoidance concept employs nested "core" and "avoid" polygons around convective weather cells, and the simulations assess the effectiveness of various avoid polygon sizes in the presence of different weather patterns, using traffic scenarios representing approximately two times the current traffic density in en-route airspace.Results from the simulation experiment show that the weather avoidance concept is effective over a wide range of weather patterns and cell speeds. Avoid polygons that are only 2-3 miles larger than their core polygons are sufficient to account for weather uncertainties in almost all cases, and traffic separation performance does not appear to degrade with the addition of weather polygon avoidance. Additional "lessons learned" from the batch simulation study are discussed in the paper, along with insights for improving the weather avoidance concept.

Section: Simulation Platformmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integration of weather avoidance and traffic separation

2011 IEEE/AIAA 30th Digital Avionics Systems Conference

Chamberlain

Wilson

2011

“…The airborne conflict management system used in this experiment series is the Autonomous Operations Planner (AOP), a NASA-developed research model of an airborne automation system built for the study of advanced distributed air-ground operational concepts 7 . The AOP provides an integrated suite of capabilities for managing traffic conflicts and trajectory changes from the flight deck perspective, including conflict detection, resolution, prevention, and trajectory constraint conformance.…”

Section: B Airborne Conflict Management Systemmentioning

confidence: 99%

“…These decision aids rely on data-linked, broadcast surveillance information that includes aircraft velocity vectors and limited flight plan information through a surveillance capability such as the Automatic Dependent Surveillance -Broadcast (ADS-B) 6 . The automation is designed to detect conflicts between aircraft and generate conflict resolution routes and conflict-free maneuvering advisories 7,8,9 . Until now, safety evaluation of SA applications has, for the most part, been based on studies using simulation tools that seldom include models of system uncertainties 10,11,12 and often make many simplifying assumptions such as perfect navigation performance and absence of prediction errors or off-nominal conditions.…”

Section: Introductionmentioning

confidence: 99%

Impact of Pilot Delay and Non-Responsiveness on the Safety Performance of Airborne Separation

The 26th Congress of ICAS and 8th AIAA ATIO

Hoadley

Wing

et al. 2008

Assessing the safety effects of prediction errors and uncertainty on automationsupported functions in the Next Generation Air Transportation System concept of operations is of foremost importance, particularly safety critical functions such as separation that involve human decision-making. Both ground-based and airborne, the automation of separation functions must be designed to account for, and mitigate the impact of, information uncertainty and varying human response. This paper describes an experiment that addresses the potential impact of operator delay when interacting with separation support systems. In this study, we evaluated an airborne separation capability operated by a simulated pilot. The experimental runs are part of the Safety Performance of Airborne Separation (SPAS) experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assistance systems. Pilot actions required by the airborne separation automation to resolve traffic conflicts were delayed within a wide range, varying from five to 240 seconds while a percentage of randomly selected pilots were programmed to completely miss the conflict alerts and therefore take no action. Results indicate that the strategic ASAS functions exercised in the experiment can sustain pilot response delays of up to 90 seconds and more, depending on the traffic density. However, when pilots or operators fail to respond to conflict alerts the safety effects are substantial, particularly at higher traffic densities. Nomenclature

“…The airborne conflict management system used in this experiment series is the Autonomous Operations Planner (AOP), a NASA-developed research model of an airborne automation system built for the study of advanced distributed air-ground operational concepts 10 . The AOP provides an integrated suite of capabilities for managing traffic conflicts and trajectory changes from the flight deck perspective, including conflict detection, resolution, prevention, and trajectory constraint conformance.…”

Section: B Airborne Conflict Management Systemmentioning

confidence: 99%

Safety Performance of Airborne Separation: Preliminary Baseline Testing

7th AIAA ATIO Conf, 2nd CEIAT Int'l Conf on Innov and Integr in Aero Sciences,17th LTA Systems Tech Conf; Followed by 2nd TEOS

Hoadley²,

Wing³

et al. 2007

The Safety Performance of Airborne Separation (SPAS) study is a suite of Monte Carlo simulation experiments designed to analyze and quantify safety behavior of airborne separation. This paper presents results of preliminary baseline testing. The preliminary baseline scenario is designed to be very challenging, consisting of randomized routes in generic high-density airspace in which all aircraft are constrained to the same flight level. Sustained traffic density is varied from approximately 3 to 15 aircraft per 10,000 square miles, approximating up to about 5 times today's traffic density in a typical sector. Research at high traffic densities and at multiple flight levels are planned within the next two years. Basic safety metrics for aircraft separation are collected and analyzed. During the progression of experiments, various errors, uncertainties, delays, and other variables potentially impacting system safety will be incrementally introduced to analyze the effect on safety of the individual factors as well as their interaction and collective effect. In this paper we report the results of the first experiment that addresses the preliminary baseline condition tested over a range of traffic densities. Early results at five times the typical traffic density in today's NAS indicate that, under the assumptions of this study, airborne separation can be safely performed. In addition, we report on initial observations from an exploration of four additional factors tested at a single traffic density: broadcast surveillance signal interference, extent of intent sharing, pilot delay, and wind prediction error. Nomenclature